E-Business Strategy Topic Five: Knowledge Management

What Is KM?

Knowledge management: The systematic generation, collection, transformation, embedding, protection, distribution and use of organisational knowledge assets.

The overall KM cycle of effective organisations: At the start, data is collected about organisational activities such as sales, new product development, etc. The data is codified and stored. Next, the data is collated, integrated and mined for significant elements and becomes information. When the information is interpreted in a suitable context — such as the current business environment (which may be different from the environment when or where the information was gathered) — it is given valuable meaning and becomes knowledge. Finally, when an enterprise acts to take advantage of that knowledge it is demonstrating wisdom, and in the process creates more data to collect and continue the cycle.

Collect Data -> Collate Information -> Interpret Knowledge -> Act with Wisdom -> Collect Data

Clearly, current KM practice is focused on business intelligence, where systems (including people) collect, organise, analyse, retrieve and interact with knowledge assets in a proactive way to help solve specific problems at any time. The purpose of these activities is to add value for the organisation and its stakeholders.

Brief History: pre-1995 Group Memory Systems; 1995-2000 Corporate intranets and Decision Support Portals; Late 1990s - Present Extranets and inter-enterprise portals; Present - Business intelligence.

Much of the literature on KM acknowledges that organisational knowledge exists in two forms: explicit and tacit.

Explicit knowledge is expressed in words and numbers and has been codified and recorded.

Tacit (or implicit) knowledge is not easily visible and expressible. It is highly personal and hard to formalise. Often, it is seen as 'expertise' and 'experience.' It has not been codified and is not recorded—but rather, is in people's heads or is evidenced in, for example, the advanced design of a new product. The same piece of knowledge may be explicit in one enterprise or group, but tacit in another.

However, while this can be a useful categorisation of knowledge, Casselman and Samson (2005) describe four additional important characteristics of knowledge that an organisation should manage and suggests actions to be taken:

1. Knowledge validity: validity based on (i) the thoroughness of the justification that is provided, or (ii) the credentials of the supplier, or (iii) congruence with current beliefs—that is, from existing knowledge.

Knowledge occurs in five categories of decreasing validity: knowledge (actual knowledge); knowledge of the first degree (knowledge except that the person lacks confidence in it); knowledge where reasons or credentials are deficient; knowledge where reasons or credentials are fairly good, but the statement itself is actually false; and ignorance, or, a pure guess. Management action: Plan and monitor the validity of knowledge that is incorporated into your KMS.

2. Social aspects of knowledge: Knowledge achieves value only in its transmission and distribution in society (even if that's confined within a single enterprise). In part, the KM cycle is a social activity. Management action: Manage how knowledge is shared, by whom and in what manner and context. Plan to ensure that the social aspects of transmission don't unintentionally devalue the knowledge.

3. Temporal (time) aspects of knowledge: There are two ways of looking at time as it relates to knowledge. Firstly, in a simple past/present/future timeline, knowledge displays three key aspects: the traditional interpretations and assumptions made about the knowledge; the paths by which the knowledge is shared and who therefore influences the knowledge over time; and anticipation of future knowledge to be gained. Secondly, time not only influences our own knowledge, but the knowledge of others around us; knowledge external to the individual or organisation. The key aspect of knowledge revealed in this view is its natural decay—knowledge tends to be forgotten unless it is deliberately maintained. Management action: Be aware of how time influences the interpretation of knowledge. Plan to revitalise and renew knowledge so as to minimise its decay.

4.Knowledge heterogeneity: There are several dimensions of knowledge management heterogeneity. These include— depth of meaning: from raw data to collated information to interpreted knowledge to actioned wisdom. physical representation: codification of knowledge typically means codification in the form of a document or information in a computer system. However, knowledge can also be 'codified' in physical forms such as software or tangible products. Ownership: may be individual, group, organisation, inter-organisation, industry, national or global.

The Value of KM

There is operational knowledge about how to build the products (goods or services), knowledge about markets in which the products may be offered, knowledge about suppliers, competitors, HR management, project management, finance, and so on. Some knowledge will be very specific to your own organisation, while other forms of knowledge will be general 'best practice' expertise.

Indeed, knowledge of effective e-business strategy is itself a knowledge asset.

All KM value is underpinned by just two fundamental drivers, which in turn allow managers to take advantage of key trends in the competitive environment. The two fundamental business drivers of KM value are:

1. Effectiveness: Finding solutions to problems, whether reactive or proactive, and providing greater value across the value chain—doing the right things.

2. Efficiency: Improving organisational structures and operations in a way that diminishes costs or improves speed and cycle times—doing things right.

Management can make much better and timelier decisions by integrating KM practices in their e-business strategies when addressing any of these major business trends. For example, KM practices can help increase manufacturing efficiency, promote better understanding and response to customer needs, and build flexibility and quality into decision-making. In summary, KM practices help unlock value across the value chain.

In previous topics we have emphasised the importance of integration and interoperability across an enterprise, and between enterprises. KM is no exception! Knowledge management is not an activity that is conducted in isolation from other activities. In fact, KM is best integrated with other core enterprise systems and activities—enterprise resource planning (ERP), supply chain management (SCM), customer relations management (CRM), and so on.

Planning for KM

When planning how to include KM in an organisation's e-business strategy, several key issues need to be addressed. Firstly, appropriate and adequate infrastructure and access is necessary to be able to capture, store, analyse and disseminate knowledge. Secondly, knowledge creates maximum value when KM efforts are integrated across the enterprise rather than operated in discrete silos. Thirdly, data mining systems are used to uncover new knowledge that would most likely otherwise go undiscovered and unused.

KM infrastructure (data repositories, back-end and front-end systems in is the foundation upon which KM solutions are built. It consists of the population and management of the repositories for unstructured data (document and content management) and structured data (data warehousing generation and management).

KM access systems (access channel and devices in Figure 4.3) extend the KM foundation infrastructure to provide individual and group access to knowledge. They consist of enterprise information portals (EIPs) and advanced searching and Web-based query for providing access to both structured and unstructured data, augmented by KM tools.

An organisation can explicitly capture and store data from identified sources. However, that is different from capturing knowledge. Many organisations collect a vast amount of data, yet are unaware of the knowledge that lies within, waiting to be discovered. Knowledge can be discovered in these data repositories by data mining.

Mining of structured data uses integrated or add-on database mining and reporting software. Data in the corporate database repository is sliced and diced (e.g. by region, time period, customer type, product category, etc) and statistically analysed for correlations.

Mining of unstructured data is accomplished with specialist software called a 'discovery engine'. A discovery engine trawls text-based document repositories and creates complex yet easy-to-use indexes, categorisations and concept maps. While a discovery engine does provide a means of locating documents, it is not its primary value. A discovery engine automatically extracts valuable and relevant textual data and then provides a navigable index.

KM Strategy

Few KM initiatives seem to deliver the results expected of them. Much of the time this is because there are no stated objectives! This is our first major lesson: any KM initiative—like any other e-business initiative—must start with specific, written objectives. Whatever objectives you set, they should be SMART—specific, measurable, actionable, realistic and time-based. With SMART (Specific; Measurable; Attainable; Relevant; Timely) objectives, you will be able to readily determine how well you met the critical success factors for KM in your organisation.

Unlike most other types of information systems, the value of using a KMS is often distant from the time of its actual use. A KMS that is mined for information on e-business competitors may yield visible benefits only once a competitive reactive strategy has been developed, implemented and measured.

If KM is so important to enterprise effectiveness, how does it get continued commitment in a busy and cluttered organisational environment, and especially where tangible results may occur long after the KM investment is commenced? The answer is that KM needs a champion; someone to spearhead KM strategy and implementation.

This is the Chief Knowledge Office who must manage all stages of the knowledge lifecycle. Critical aspects of their role are to:
encourage people to contribute and use knowledge; encourage individual learning and innovative thinking; implement reward plans and incentives; determine what technology is needed for the knowledge management effort and implement it; put processes in place to facilitate organisational learning measure the impact of KM on the business.

While the KM strategic plan should define the overall value architecture and objectives for these assets, the design plan should define a clear process of knowledge management. Oppong et al. (2005) recommend the following process (with some suggested software tools):

1. Knowledge creation and capture. Performed by both humans and software agents, this is a formal process of acquiring the knowledge from the source.

2. Knowledge organisation and storage. Categorisation, indexing, standardisation and navigation contribute to the effectiveness of knowledge retrieval and distribution.

3. Knowledge retrieval. Mining, searching and fulfilling specific information requests to identify key issues, patterns or trends.

4. Collaboration and workflow. Span a range of activities from ad hoc email and common access to documents, to more structured systems for document creation, approval, publication and use.

5. Distribution. The transfer of knowledge to users by push, publishing or notification methods.

6. Assimilation. Facilitate the interpretation, summarisation, visualisation, explanation and exploration of information.

7. Transformation. Provide the ability to treat a collection of semi-structured documents as though they were in a relational database.

Risk Management

Objectives: Remember that the majority of KM projects fail, and a major reason is that they start out with no specific objectives. Ensure your KM initiatives have specific, clear and measurable objectives.

Motivation: Your employees need be motivated in the same direction as your organisation. Organisation mission and employee value statements are only part of the solution.

Resources: Furthermore, the extent of the change in people management requirements might catch human resource executives off balance.

Legal changes: Changes to legislation will characterise the knowledge era.

Appropriate ROI: The level of investment needs to be proportionate to the level of return (as is the case for any asset investment).

Implications for Managers

To maximise KM effectiveness, managers should keep the following in mind:

* knowledge is an organisational asset to be valued, captured and maintained

* the key drivers of KM and the benefits that can be achieved, such as improved productivity, happier customers, reduced costs, more streamlined business processes and faster response to key business issues

* drive KM from the top and make sure that KM serves the business strategy, rather than having business strategy be a slave to KM technology

* appoint and support a Chief Knowledge Officer

* understand the social and cultural aspects of knowledge and plan initiatives to effectively drive KM adoption and use throughout the enterprise

* when creating the KM design plan, follow the specific seven-point process to ensure the system will maximise value during live operations.

* integrate cross-functional systems to leverage higher knowledge asset value than from

* isolated knowledge islands

* manage KM risk.


* There are no incentives or sanctions to promote sharing information and insights among employees

* Little time or attention is given to identify the lessons learned from project failures and successes

* Assumptions about new projects or activities are not challenged. These are executed based on expectations and not on realizations

* The organization hires and promotes individuals based on technical expertise alone

* Management is reluctant to talk about projects that did not work well ("sharing our failures")

* The different missions and visions of divisions or departments produce different cultures that seem to succeed only in antagonizing each other.